Most AI tools work like a “damage category guesser.” You enter basic facts (injury type, treatment length, bills), and the tool returns an informal range.
That can be helpful for calming uncertainty. It can also be dangerously incomplete.
In local practice, the biggest gaps are usually:
- Causation details: whether the care fell below the accepted standard and whether that specific failure caused your harm.
- Documentation quality: missing notes, delayed follow-up, or inconsistent charting can shift how strong a claim is.
- Treatment timeline clarity: if your condition worsened while care was delayed or incomplete, the exact sequence matters.
- Injury impact proof: limitations affecting daily life or work often need supporting records, not just your description.
AI can’t see what a case file reveals—like diagnostic reasoning, missed red flags, or whether a provider acted appropriately given the symptoms recorded at the time.


